Reputation: 103
I have tried different solutions where similar questions where made, but didn't get the expected result, so far.
I have two dataframes, df1
and df2
, where both of them contain a column named 'fb rq id'
.
There are far more lines in df2
than in df1
, and I want to check which values from df2['fb rq id']
are in df1['fb rq id']
and how many times it appears there, creating a column on df2
with the number of times the value on that line is in df1
.
If you know how to create a column with just binary information wether df2.['fb rq id']
is in df1['fb rq id']
, that also helps.
Thank you!!
Upvotes: 0
Views: 1004
Reputation: 102
how about this?
df2['count_from_df1'] = [list(df1['fb rq id']).count(id)
if id in df1['fb rq id'] else 0
for id in df2['fb rq id']]
Upvotes: 1